fix period plot generation after rework

generate_latex_table.py

@@ -0,0 +1,31 @@
+import pandas as pd
+from main.astrodatagui.db.StarsDB import StarDB
+
+db: StarDB = StarDB.getInstance("stars.db")
+starMainIDs = db.getAllStars()
+res = []
+for mainID in starMainIDs:
+    altNames = db.getStarAltNames(mainID)
+    infos = db.getStarInfos(mainID)
+    kicName = "-"
+    ticName = "-"
+    spType = "-"
+    for name in altNames:
+        if name[0].startswith("TIC"):
+            ticName = name[0]
+        if name[0].startswith("KIC"):
+            kicName = name[0]
+    spType = infos["SpType"]
+    res.append({"MainID": mainID,
+    "Spectral Type": spType,
+    "TIC": ticName,
+    "KIC": kicName})
+
+resDF = pd.DataFrame(res)
+resDF.sort_values(by=["Spectral Type", "MainID"]) #.to_latex(index=False)
+
+for sptype in ["M", "K", "G", "F"]:
+    texFile = open(f"table_{sptype}.tex", "w")
+    tex = resDF[resDF["Spectral Type"].str.startswith(sptype)].sort_values(by=["Spectral Type", "MainID"]).to_latex(index=False)
+    texFile.write(tex)
+    texFile.close()

generate_plots.py

@@ -86,6 +86,8 @@ def plotBinsHistogram(PDCSAPdataList, PDCSAPlabelList, PDCSAPcolorList, bins, ti
             axHistoPhase.plot(fit[0], fit[1], color="blue")
         fitCol = [fit[1] for fit in foldedFits]
         fitCol = np.array(list(itertools.chain.from_iterable(fitCol)))
+        if(len(fitCol) == 0):
+            fitCol = np.array([0, 1])
         axHistoPhase.set_ylim(np.min(fitCol), np.max(fitCol)*1.2)
 
     plt.savefig(filename)
@@ -246,9 +248,7 @@ def plotStarPeriod(data, showSourceFilter, folderPath, starName):
     nameFilter &= showSourceFilter
     finalData = pd.concat([finalData, data[nameFilter]], ignore_index=True)
 
-    pdcsapbinningData = []
     pdcsapbinningDataSpotModDiffPeriod = []
-    foldedFits = []
     foldedPeriodFits = []
     locFolder = f"{folderPath}/stars/{starNameR}/"
     mkdir_p(f"{locFolder}/")
@@ -265,12 +265,12 @@ def plotStarPeriod(data, showSourceFilter, folderPath, starName):
                     normPhase = normalizePhase(td.value, np.abs(PDCSAPminOrigPhase), np.abs(PDCSAPmaxOrigPhase))
                     csvFile.write(f"{row['StarName']},{row['SpType']},{row['Source']},{row['FilePath']},{pv['FlarePeakTime']},{pv['FlarePeak']},{row['pdcsapPeriod']},{row['pdcsapSpotModulation']},{normPhase},{peak['FlarePeak']}")
                     csvFile.write("\n")
-                    pdcsapbinningData.append({"SpType": f'{row["SpType"][0:2] if len(row["SpType"]) > 1 else row["SpType"][0]}',
+                    pdcsapbinningDataSpotModDiffPeriod.append({"SpType": f'{row["SpType"][0:2] if len(row["SpType"]) > 1 else row["SpType"][0]}',
                                             "PDCSAPNormPhasePeriod": normPhase,
                                             "PeakPeriod": peak["FlarePeak"]})
                     if(peak["FlarePeak"] > 100):
                         print(row["StarName"], "has over 100 peak")
-                foldedFits.append([normalizePhase(row["pdcsapFoldedFitPhase"]), row["pdcsapFoldedFit"]])
+                foldedPeriodFits.append([normalizePhase(row["pdcsapFoldedFitPhase"]), row["pdcsapFoldedFit"]])
 
     csvFile.close()
     pdcsapbinningDataSpotModDiffPeriod = pd.DataFrame(pdcsapbinningDataSpotModDiffPeriod) if len(pdcsapbinningDataSpotModDiffPeriod) > 0 else None